Cluster-randomized, controlled trial of computer-based decision support for selecting long-term anti-thrombotic therapy after acute ischaemic stroke

Abstract

Background: Identifying the appropriate long‐term anti‐thrombotic therapy following acute ischaemic stroke is a challenging area in which computer‐based decision support may provide assistance. Aim: To evaluate the influence on prescribing practice of a computer‐based decision support system (CDSS) that provided patient‐specific estimates of the expected ischaemic and haemorrhagic vascular event rates under each potential anti‐thrombotic therapy. Design: Cluster‐randomized controlled trial. Methods: We recruited patients who presented for a first investigation of ischaemic stroke or TIA symptoms, excluding those with a poor prognosis or major contraindication to anticoagulation. After observation of routine prescribing practice (6 months) in each hospital, centres were randomized for 6 months to either control (routine practice observed) or intervention (practice observed while the CDSS provided patient‐specific information). We compared, between control and intervention centres, the risk reduction (estimated by the CDSS) in ischaemic and haemorrhagic vascular events achieved by long‐term anti‐thrombotic therapy, and the proportions of subjects prescribed the optimal therapy identified by the CDSS. Results: Sixteen hospitals recruited 1952 subjects. When the CDSS provided information, the mean relative risk reduction attained by prescribing increased by 2.7 percentage units (95%CI −0.3 to 5.7) and the odds ratio for the optimal therapy being prescribed was 1.32 (0.83 to 1.80). Some 55% (5/9) of clinicians believed the CDSS had influenced their prescribing. Conclusions: Cluster‐randomized trials provide excellent frameworks for evaluating novel clinical management methods. Our CDSS was feasible to implement and acceptable to clinicians, but did not substantially influence prescribing practice for anti‐thrombotic drugs after acute ischaemic stroke.